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Including indigenous knowledge in species distribution modeling for increased ecological insights
Author(s) -
Skroblin Anja,
Carboon Tracy,
Bidu Gladys,
Chapman Nganjapayi,
Miller Minyawu,
Taylor Karnu,
Taylor Waka,
Game Edward T.,
Wintle Brendan A.
Publication year - 2021
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/cobi.13373
Subject(s) - threatened species , indigenous , traditional knowledge , geography , occupancy , ecology , distribution (mathematics) , species distribution , habitat , environmental resource management , biology , environmental science , mathematical analysis , mathematics
Indigenous knowledge systems hold detailed information on current and past environments that can inform ecological understanding as well as contemporary environmental management. Despite its applicability, there are limited examples of indigenous knowledge being incorporated in species distribution models, which are widely used in the ecological sciences. In a collaborative manner, we designed a structured elicitation process and statistical framework to combine indigenous knowledge with survey data to model the distribution of a threatened and culturally significant species (greater bilby or mankarr [ Macrotis lagotis ]). We used Martu (Aboriginal people of the Australian western deserts) occurrence knowledge and presence data from track‐based surveys to create predictive species distribution models with the Maxent program. Predictions of species distribution based on Martu knowledge were broader than those created with survey data. Together the Martu and survey models showed potential local declines, which were supported by Martu observation. Both data types were influenced by sampling bias that appeared to affect model predictions and performance. Martu provided additional information on habitat associations and locations of decline and descriptions of the ecosystem dynamics and disturbance regimes that influence occupancy. We concluded that intercultural approaches that draw on multiple sources of knowledge and information types may improve species distribution modeling and inform management of threatened or culturally significant species.